appthreat-chen

v2.5.22 suspicious
6.0
Medium Risk

Code Hierarchy Exploration Net (chen)

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has moderate risk due to potential misuse of credentials and a suspicious non-HTTPS link, despite standard network calls and minimal obfuscation.

  • High credential risk due to GITHUB_TOKEN retrieval
  • Suspicious non-HTTPS link in metadata
Per-check LLM notes
  • Network: Network calls seem standard for interacting with external services or APIs.
  • Shell: Shell executions might indicate package installation or system configuration, but could pose risks if not properly controlled.
  • Obfuscation: No obfuscation patterns detected in the provided code snippet.
  • Credentials: The code retrieves and uses a GITHUB_TOKEN from environment variables, which could indicate legitimate API usage but also poses a risk if not properly secured.
  • Metadata: Suspicious non-HTTPS link found, but no other red flags.

📦 Package Quality Overall: Low (4.6/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (9701 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 7 type-annotated function signatures (partial)
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 4 unique contributor(s) across 100 commits in AppThreat/chen
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

  • _url.rstrip("/") client = httpx.Client(base_url=base_url, auth=auth, timeout=CLIENT_TIMEOUT) at
  • _url: atomgenclient = httpx.Client(base_url=atomgen_url, timeout=CLIENT_TIMEOUT) return Con
  • _url.rstrip("/") client = httpx.AsyncClient(base_url=base_url, auth=auth, timeout=CLIENT_TIMEOUT) at
  • _url: atomgenclient = httpx.AsyncClient(base_url=atomgen_url, timeout=CLIENT_TIMEOUT) ws_url = f
  • packages scope") client = httpx.Client(http2=True, follow_redirects=True, timeout=180) r = clie
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 6.0

Found 3 shell execution pattern(s)

  • otal=100) subprocess.check_call( line.split(" "),
  • exists(req_file): subprocess.check_call( [sys.executable, "-m", "pip", "install", "-
  • lib_dir, py_version cp = subprocess.run( ["python3-config", "--ldflags", "--embed"],
⚠ Credential Harvesting score 2.5

Found 1 credential access pattern(s)

  • hub.com/graphql") api_token = os.getenv("GITHUB_TOKEN") headers = {"Authorization": f"token {api_token}"} ecosys
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: appthreat.com

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://127.0.0.1:9999/tree?token=chennai
✓ Git Repository History

Repository AppThreat/chen appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Team AppThreat" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with appthreat-chen 
Develop a code analysis tool named 'CodeExplorer' using Python that leverages the 'appthreat-chen' package for exploring and visualizing the hierarchical structure of source code files. This tool will help developers understand complex codebases more intuitively by providing a graphical representation of the relationships between different code modules and functions. Here’s a detailed outline of the project:

1. **Project Setup**: Create a virtual environment for your project and install necessary dependencies including 'appthreat-chen'. Ensure you have a clean setup with a requirements.txt file for dependency management.

2. **Core Functionality**:
   - Integrate 'appthreat-chen' to parse and analyze the input codebase, extracting the hierarchy of classes, functions, and modules.
   - Develop a function to convert this hierarchical data into a format suitable for visualization (e.g., JSON).

3. **Visualization**:
   - Use a library like Plotly or D3.js to create an interactive graph that displays the relationships between different components of the codebase.
   - Implement tooltips and hover effects to provide additional information about each node in the graph when clicked or hovered over.

4. **User Interface**:
   - Design a simple yet effective web-based interface where users can upload their codebase.
   - Include options for selecting specific directories or files within the uploaded codebase for analysis.

5. **Advanced Features**:
   - Implement a feature to filter the displayed hierarchy based on user-defined criteria (e.g., show only classes that inherit from a specific base class).
   - Add support for exporting the visualized hierarchy as an image or a PDF document.

6. **Testing & Documentation**:
   - Write unit tests to ensure the accuracy of the parsed hierarchy and the functionality of the visualization tools.
   - Provide comprehensive documentation explaining how to use 'CodeExplorer', including examples of its usage with different types of codebases.

7. **Deployment**:
   - Package your application as a standalone executable or a Docker container for easy deployment.
   - Deploy your application on a cloud service provider such as AWS or Heroku so that it can be accessed via a web URL.

This project aims to demonstrate the power of 'appthreat-chen' in simplifying the understanding of large-scale software projects through visual and interactive means.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!